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Evidence record 4898 · automatically gathered

Driver-WM: A Driver-Centric Traffic-Conditioned Latent World Model for In-Cabin Dynamics Rollout

Safe L2/L3 driving automation requires anticipating human-in-the-loop reactions during shared-control transitions. While most driving world models forecast the external environment, in-cabin intelligence remains strictly recognition-oriented and lacks multi-step rollout capabilities for driver dynamics. We introduce Driver-WM, a driver-centric latent world model that rolls out in-cabin dynamics causally conditioned on out-cabin traffic context. This formulation unifies physical kinematics foreca

Record details

Published: 6 May 2026
Source: arXiv
Category: Research
Topics: Jobs & economy · Environment
Retrieved: 14 July 2026

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How to cite this record

ethics.ai (6 May 2026), “Driver-WM: A Driver-Centric Traffic-Conditioned Latent World Model for In-Cabin Dynamics Rollout,” evidence record 4898, https://ethics.ai/record/4898 (originally published by arXiv).

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